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Optimizing Stock Market Prediction Using Long Short-Term Memory Networks: 《Journal of Computer and Communications》2025年第2期207-222,共16页Nadia Afrin Ritu Samsun Nahar Khandakar Md. Masum Bhuiyan Md. Imdadul Islam; Deep learning plays a vital role in real-life applications, for example object identification, human face recognition, speech recognition, biometrics identification, and short and long-term forecasting of data. The ma...; 关键词：Long Short-Term Memory (LSTM) Stock Market PREDICTION Time Series Analysis Deep Learning

Forecasting returns with machine learningand optimizing global portfolios:evidencefrom the Korean and U.S.stock markets: 《Financial Innovation》2024年第1期64-93,共30页Dohyun Chun Jongho Kang Jihun Kim; supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea(NRF-2022S1A5A8055710).; This study employs a variety of machine learning models and a wide range of economic and financial variables to enhance the forecasting accuracy of the Korean won–U.S.dollar(KRW/USD)exchange rate and the U.S.and Kore...; 关键词：International asset allocation Foreign exchange rate Stock marketprediction Portfolio diversifcation Machine learning

Feature selection with annealing for forecasting financial time series: 《Financial Innovation》2024年第1期201-226,共26页Hakan Pabuccu Adrian Barbu; supported by THE SCIENTIFIC AND TECHNOLOGICAL RESEARCH COUNCIL OF TURKIYE.; Stock market and cryptocurrency forecasting is very important to investors as they aspire to achieve even the slightest improvement to their buy-or-hold strategies so that they may increase profitability.However,obtai...; 关键词：Financial time-series forecasting Feature selection Machine learning Cryptocurrency Stock market Return forecasting

Do earthquakes shake the stock market? Causal inferences from Turkey's earthquake: 《Financial Innovation》2024年第1期227-245,共19页Khalid Khan Javier Cifuentes-Faura Muhammad Shahbaz; This study’s main purpose is to use Bayesian structural time-series models to investigate the causal effect of an earthquake on the Borsa Istanbul Stock Index.The results reveal a significant negative impact on stock...; 关键词：Stock market EARTHQUAKE Causal inference Bayesian structural time-series Counterfactual predicting

The Dynamics of Tail Risk in the Chinese Stock Market: An Empirical Study Using the LCARE Model: 《Journal of Systems Science and Information》2024年第6期709-731,共23页Feipeng ZHANG Yuhan MA Di YUAN; Supported by the Natural Science Foundation of Shandong Province(ZR2023MG037);the National Natural Science Foundation of China(72171192)。; This study presents a comprehensive and innovative analysis of dynamic tail risk in the Chinese stock market utilizing the localizing conditional autoregressive expectiles(LCARE)model.We consider the dynamic changes i...; 关键词：tail risk LCARE model time-varying parameters portfolio insurance strategy stock market

Complex network analysis of global stock market co-movement during the COVID-19 pandemic based on intraday open-high-low-close data: 《Financial Innovation》2024年第1期4031-4080,共50页Wenyang Huang Huiwen Wang Yigang Wei Julien Chevallier; the financial support from the Beijing Municipal Social Science Foundation(No.20GLC054);the National Natural Science Foundation of China(Nos.72021001,72174020,71904009);the Natural Science Foundation of Beijing Municipality(No.9232014);the Humanities and Social Science Fund of Ministry of Education of China(No.18YJC840041).; This study uses complex network analysis to investigate global stock market co-movement during the black swan event of the Coronavirus Disease 2019(COVID-19)pandemic.We propose a novel method for calculating stock pri...; 关键词：Complex network Stock market co-movement OHLC data Degree centrality analysis

Google search volume index and investor attention in stock market: a systematic review: 《Financial Innovation》2024年第1期703-731,共29页María José Ayala Nicolás Gonzálvez-Gallego Rocío Arteaga-Sánchez; This study systematically reviewed the literature on using the Google Search Volume Index(GSVI)as a proxy variable for investor attention and stock market movements.We analyzed 56 academic studies published between 20...; 关键词：Google Trends GSVI Investor attention Stock market forecasting

An interval constraint-based trading strategy with social sentiment for the stock market: 《Financial Innovation》2024年第1期2768-2798,共31页Mingchen Li Kun Yang Wencan Lin Yunjie Wei Shouyang Wang; partly supported by the National Natural Science Foundation of China under Grants No.72171223,No.71801213,and No.71988101;the National Key R&D Program of China under Grants No.2021ZD0111204。; Developing effective strategies to earn excess returns in the stock market is a cutting-edge topic in the field of economics.At the same time,stock price forecasting that supports trading strategies is considered one ...; 关键词：Stock price forecasting Deep learning Sentiment analysis Trading strategy COVID-19 era

Applying AI Models for Stock Investment Decisions: 《Open Journal of Applied Sciences》2024年第11期3061-3068,共8页Diya Shiburam; In the realm of finance and economics, the search for reliable stock predictions remains a focal point for researchers [1]. Contrary to common belief, stock market prices are not merely random guesses, but rather powe...; 关键词：Stock Market TRADING Artificial Intelligence FINANCE

Deep Learning-Based Stock Price Prediction Using LSTM Model: 《Proceedings of Business and Economic Studies》2024年第5期176-185,共10页Jiayi Mao Zhiyong Wang; The stock market is a vital component of the broader financial system,with its dynamics closely linked to economic growth.The challenges associated with analyzing and forecasting stock prices have persisted since the ...; 关键词：Autoregressive integrated moving average(ARIMA)model Long Short-Term Memory(LSTM)network Forecasting Stock market

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